high performance computing on graphics processing units: hgpu.org

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A GPU-based implementation for Range Queries on Spaghettis Data Structure

Roberto Uribe-Paredes, Pedro Valero-Lara, Enrique Arias, Jose L. Sanchez, Diego Cazorla

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 285

January 23, 2012 by hgpu

Revision of Relational Joins for Multi-Core and Many-Core Architectures

Martin Krulis, Jakub Yaghob

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Tags: Algorithms, Computer science, CUDA, Databases, Join, nVidia, nVidia GeForce GTX 580

January 22, 2012 by hgpu

OpenCL for Database Query Processing

Georgios Krespis

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Tags: Algorithms, Computer science, Databases, nVidia, nVidia GeForce 9600 M, OpenCL, Thesis

January 21, 2012 by hgpu

Parallel Optimization of Queries in XML Dataset Using GPU

Xujie Si, Airu Yin, Xiaocheng Huang, Xiaojie Yuan, Xiaoguang Liu, Gang Wang

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, Optimization

January 18, 2012 by hgpu

LNA: Fast Protein Classification Using A Laplacian Characterization of Tertiary Structure

Nicolas Bonnel, Pierre-Francois Marteau

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Tags: Algorithms, Benchmarking, Biology, Databases, nVidia, OpenCL, Tesla M2050

January 18, 2012 by hgpu

Nested Intervals Tree Encoding with System of Residual Classes

A. Malikov, A. Turyev

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia

January 16, 2012 by hgpu

Efficient Knowledge Extraction from Structured Data

Bianca Wackersreuther

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Tags: Algorithms, Clustering, Compression, Computer science, CUDA, Data mining, Databases, Heterogeneous systems, Hierarchical clustering, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Thesis

January 14, 2012 by hgpu

A Nearest Neighbor Data Structure for Graphics Hardware

Lawrence Cayton

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Databases, Nearest neighbour, nVidia, Tesla C2050

January 11, 2012 by hgpu

Top-k Queries Processing With Uncertain Data on Graphics Processing Units

Haozhe Chang, Tingting Qin, Xiaoguang Liu, Gang Wang, Airu Yin

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480

January 9, 2012 by hgpu

Fast GPU-based Locality Sensitive Hashing for K-Nearest Neighbor Computation

Jia Pan, Dinesh Manocha

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Tags: Algorithms, Computer science, Data mining, Databases, Hashing, Nearest neighbour, nVidia, nVidia GeForce GTX 480

January 9, 2012 by hgpu

GPU-accelerated Chemical Similarity Assessment for Large Scale Databases

Marco Maggioni, Marco Domenico Santambrogio, Jie Liang

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Tags: Algorithms, Chemistry, CUDA, Databases, nVidia, nVidia GeForce 9400 M, nVidia GeForce GTX 460, Optimization

December 27, 2011 by hgpu

Designing Fast Architecture Sensitive Tree Search on Modern Multi-Core/Many-Core Processors

Changkyu Kim, Jatin Chhugani, Nadathur Satish, Eric Sedlar, Anthony D. Nguyen, Tim Kaldewey, Victor W. Lee, Scott A. Brandt, Pradeep Dubey

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Tags: Compression, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 280, Search, Tesla C2050

December 25, 2011 by hgpu

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

See all packages

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high performance computing on graphics processing units: hgpu.org

A GPU-based implementation for Range Queries on Spaghettis Data Structure

Revision of Relational Joins for Multi-Core and Many-Core Architectures

OpenCL for Database Query Processing

Parallel Optimization of Queries in XML Dataset Using GPU

LNA: Fast Protein Classification Using A Laplacian Characterization of Tertiary Structure

Nested Intervals Tree Encoding with System of Residual Classes

Efficient Knowledge Extraction from Structured Data

A Nearest Neighbor Data Structure for Graphics Hardware

Top-k Queries Processing With Uncertain Data on Graphics Processing Units

Fast GPU-based Locality Sensitive Hashing for K-Nearest Neighbor Computation

GPU-accelerated Chemical Similarity Assessment for Large Scale Databases

Designing Fast Architecture Sensitive Tree Search on Modern Multi-Core/Many-Core Processors

Recent source codes

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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